|A General Methodology for Designing Self-Organizing Systems - Carlos Gershenson|
Our technologies complexify our environments. Thus, new technologies need to deal with more and more complexity. Several efforts have been made to deal with this complexity using the concept of self-organization. However, in order to promote its use and understanding, we must first have a pragmatic understanding of complexity and self-organization. This paper presents a conceptual framework for speaking about self-organizing systems...
|Towards Self-organizing Bureaucracies - Carlos Gershenson|
This paper proposes self-organization as a method to improve the efficiency and adaptability of bureaucracies and similar social systems. Bureaucracies are described as networks of agents, where the main design principle is to reduce local "friction" to increase local and global "satisfaction". Following this principle, solutions are proposed for improving communication within bureaucracies, sensing public satisfaction, dynamic modification of hierarchies, and contextualization of procedures...
|Computing Networks: A General Framework to Contrast Neural and Swarm Cognitions - Carlos Gershenson|
This paper presents the Computing Networks (CNs) framework. CNs are used to generalize neural and swarm architectures. Artificial neural networks, ant colony optimization, particle swarm optimization, and realistic biological models are used as examples of instantiations of CNs. The description of these architectures as CNs allows their comparison. Their differences and similarities allow the identification of properties that enable neural and swarm architectures to perform complex computations ...
|Updating Schemes in Random Boolean Networks: Do They Really Matter? - Carlos Gershenson|
In this paper we try to end the debate concerning the suitability of different updating schemes in random Boolean networks (RBNs). We quantify for the first time loose attractors in asyncrhonous RBNs, which allows us to analyze the complexity reduction related to different updating schemes. We also report that all updating schemes yield very similar critical stability values, meaning that the "edge of chaos" does not depend much on the updating scheme...
|Introduction to Random Boolean Networks - Carlos Gershenson|
The goal of this tutorial is to promote interest in the study of random Boolean networks (RBNs). These can be very interesting models, since one does not have to assume any functionality or particular connectivity of the networks to study their generic properties. Like this, RBNs have been used for exploring the configurations where life could emerge. The fact that RBNs are a generalization of cellular automata makes their research a very important topic...
|What Does Artificial Life Tell Us About Death? - Carlos Gershenson|
Short philosophical essay
|The Implications of Interactions for Science and Philosophy - Carlos Gershenson|
Reductionism has dominated science and philosophy for centuries. Complexity has recently shown that interactions---which reductionism neglects---are relevant for understanding phenomena. When interactions are considered, reductionism becomes limited in several aspects. In this paper, I argue that interactions imply non-reductionism, non-materialism, non-predictability, non-Platonism, and non-nihilism...
|Phase Transitions in Random Boolean Networks with Different Updating Schemes - Carlos Gershenson|
In this paper we study the phase transitions of different types of Random Boolean networks. These differ in their updating scheme: synchronous, semi-synchronous, or asynchronous, and deterministic or non-deterministic. It has been shown that the statistical properties of Random Boolean networks change considerable according to the updating scheme. We study with computer simulations sensitivity to initial conditions as a measure of order/chaos...
|Self-Organizing Traffic Lights - Carlos Gershenson|
Steering traffic in cities is a very complex task, since improving efficiency involves the coordination of many actors. Traditional approaches attempt to optimize traffic lights for a particular density and configuration of traffic. The disadvantage of this lies in the fact that traffic densities and configurations change constantly. Traffic seems to be an adaptation problem rather than an optimization problem...
|The Sigma Profile: A Formal Tool to Study Organization and its Evolution at Multiple Scales - Carlos Gershenson|
The $\sigma$ profile is presented as a tool to analyze the organization of systems at different scales, and how this organization changes in time. Describing structures at different scales as goal-oriented agents, one can define $\sigma \in [0,1]$ ("satisfaction") as the degree to which the goals of each agent at each scale have been met. $\sigma$ reflects the organization degree at that scale. The $\sigma$ profile of a system shows the satisfaction at different scales, with the possibility to s...
|The World as Evolving Information - Carlos Gershenson|
This paper discusses the benefits of describing the world as information, especially in the study of the evolution of life and cognition. Traditional studies encounter problems because it is difficult to describe life and cognition in terms of matter and energy, since their laws are valid only at the physical scale. However, if matter and energy, as well as life and cognition, are described in terms of information, evolution can be described consistently as information becoming more complex...
|Complexity - Carlos Gershenson|
There is no single definition of complexity (Edmonds 1999; Gershenson 2008; Mitchell 2009), as it acquires different meanings in different contexts. A general notion is the amount of information required to describe a phenomenon (Prokopenko et al. 2008), but it can also be understood as the length of the shortest program required to compute that description, as the time required to compute that description, as the minimal model to statistically describe a phenomenon, etc.
|Information and Computation - Carlos Gershenson|
In this chapter, concepts related to information and computation are reviewed in the context of human computation. A brief introduction to information theory and different types of computation is given. Two examples of human computation systems, online social networks and Wikipedia, are used to illustrate how these can be described and compared in terms of information and computation.
|Living in Living Cities - Carlos Gershenson|
This paper presents an overview of current and potential applications of living technology to some urban problems. Living technology can be described as technology that exhibits the core features of living systems. These features can be useful to solve dynamic problems. In particular, urban problems concerning mobility, logistics, telecommunications, governance, safety, sustainability, and society and culture are presented, while solutions involving living technology are reviewed...
|Self-organizing urban transportation systems - Carlos Gershenson|
Urban transportation is a complex phenomenon. Since many agents are constantly interacting in parallel, it is difficult to predict the future state of a transportation system. Because of this, optimization techniques tend to give obsolete solutions, as the problem changes before it can be optimized. An alternative lies in seeking adaptive solutions. This adaptation can be achieved with self-organization...
|Are Minds Computable? - Carlos Gershenson|
This essay explores the limits of Turing machines concerning the modeling of minds and suggests alternatives to go beyond those limits.
|Guiding the Self-organization of Random Boolean Networks - Carlos Gershenson|
Random Boolean networks (RBNs) are models of genetic regulatory networks. It is useful to describe RBNs as self-organizing systems to study how changes in the nodes and connections affect the global network dynamics. This article reviews eight different methods for guiding the self-organization of RBNs. In particular, the article is focussed on guiding RBNs towards the critical dynamical regime, which is near the phase transition between the ordered and dynamical phases...
|Polyethism in a colony of artificial ants - Chris Marriott|
We explore self-organizing strategies for role assignment in a foraging task carried out by a colony of artificial agents. Our strategies are inspired by various mechanisms of division of labor (polyethism) observed in eusocial insects like ants, termites, or bees. Specifically we instantiate models of caste polyethism and age or temporal polyethism to evaluated the benefits to foraging in a dynamic environment...
|Evolution of Complexity - Carlos Gershenson|
The evolution of complexity has been a central theme for Biology  and Artificial Life research . It is generally agreed that complexity has increased in our universe, giving way to life, multi-cellularity, societies, and systems of higher complexities. However, the mechanisms behind the complexification and its relation to evolution are not well understood. Moreover complexification can be used to mean different things in different contexts...
|Complexity and Information: Measuring Emergence, Self-organization, and Homeostasis at Multiple Scales - Carlos Gershenson|
Concepts used in the scientific study of complex systems have become so widespread that their use and abuse has led to ambiguity and confusion in their meaning. In this paper we use information theory to provide abstract and concise measures of complexity, emergence, self-organization, and homeostasis. The purpose is to clarify the meaning of these concepts with the aid of the proposed formal measures...
|Measuring the Complexity of Ultra-Large-Scale Adaptive Systems - Michele Amoretti|
Ultra-large scale (ULS) systems are becoming pervasive. They are inherently complex, which makes their design and control a challenge for traditional methods. Here we propose the design and analysis of ULS systems using measures of complexity, emergence, self-organization, and homeostasis based on information theory. These measures allow the evaluation of ULS systems and thus can be used to guide their design...
|Protocol Requirements for Self-organizing Artifacts: Towards an Ambient Intelligence - Carlos Gershenson|
We discuss which properties common-use artifacts should have to collaborate without human intervention. We conceive how devices, such as mobile phones, PDAs, and home appliances, could be seamlessly integrated to provide an "ambient intelligence" that responds to the user's desires without requiring explicit programming or commands. While the hardware and software technology to build such systems already exists, as yet there is no standard protocol that can learn new meanings...
|Complex Networks - Carlos Gershenson|
Introduction to the Special Issue on Complex Networks, Artificial Life journal.
|Evolution of Complexity: Introduction to the Workshop - Carlos Gershenson|
The evolution of complexity has been a central theme for Biology and Artificial Life (Bonner, 1988; Bedau et al., 2000). Complexification has been interpreted in different ways: as a process of diversification between evolving units (Bonner, 1988) or as a scaling process that is related to the idea of transitions between different levels of complexity (Smith and Szathmary, 1995). There have been previous workshops on this topic, e.g...
|Modular Random Boolean Networks - Rodrigo Poblanno-Balp|
Random Boolean networks (RBNs) have been a popular model of genetic regulatory networks for more than four decades. However, most RBN studies have been made with random topologies, while real regulatory networks have been found to be modular. In this work, we extend classical RBNs to define modular RBNs. Statistical experiments and analytical results show that modularity has a strong effect on the properties of RBNs...
|Self-organizing traffic lights at multiple-street intersections - Carlos Gershenson|
Summary: Traffic light coordination is a complex problem. In this paper, we extend previous work on an abstract model of city traffic to allow for multiple street intersections. We test a self-organizing method in our model, showing that it is close to theoretical optima and superior to a traditional method of traffic light coordination. Abstract: The elementary cellular automaton following rule 184 can mimic particles flowing in one direction at a constant speed...
|The Role of Redundancy in the Robustness of Random Boolean Networks - Carlos Gershenson|
Evolution depends on the possibility of successfully exploring fitness landscapes via mutation and recombination. With these search procedures, exploration is difficult in "rugged" fitness landscapes, where small mutations can drastically change functionalities in an organism. Random Boolean networks (RBNs), being general models, can be used to explore theories of how evolution can take place in rugged landscapes; or even change the landscapes...
|Contextual Random Boolean Networks - Carlos Gershenson|
We propose the use of Deterministic Generalized Asynchronous Random Boolean Networks [Gershenson, 2002] as models of contextual deterministic discrete dynamical systems. We show that changes in the context have drastic effects on the global properties of the same networks, namely the average number of attractors and the average percentage of states in attractors. We introduce the situation where we lack knowledge on the context as a more realistic model for contextual dynamical systems...
|Living is information processing: from molecules to global systems - Keith D. Farnsworth|
We extend the concept that life is an informational phenomenon, at every level of organisation, from molecules to the global ecological system. According to this thesis: (a) living is information processing, in which memory is maintained by both molecular states and ecological states as well as the more obvious nucleic acid coding; (b) this information processing has one overall function - to perpetuate itself; and (c) the processing method is filtration (cognition) of, and synthesis of, informa...
|Information Measures of Complexity, Emergence, Self-organization, Homeostasis, and Autopoiesis - Nelson Fernandez|
This chapter reviews measures of emergence, self-organization, complexity, homeostasis, and autopoiesis based on information theory. These measures are derived from proposed axioms and tested in two case studies: random Boolean networks and an Arctic lake ecosystem. Emergence is defined as the information produced by a system or process. Self-organization is defined as the opposite of emergence, while complexity is defined as the balance between emergence and self-organization...
|Using RDF to Model the Structure and Process of Systems - Marko A. Rodriguez|
Many systems can be described in terms of networks of discrete elements and their various relationships to one another. A semantic network, or multi-relational network, is a directed labeled graph consisting of a heterogeneous set of entities connected by a heterogeneous set of relationships. Semantic networks serve as a promising general-purpose modeling substrate for complex systems. Various standardized formats and tools are now available to support practical, large-scale semantic network mod...
|Self-organizing traffic lights: A realistic simulation - Seung-Bae Cools|
We have previously shown in an abstract simulation (Gershenson, 2005) that self-organizing traffic lights can improve greatly traffic flow for any density. In this paper, we extend these results to a realistic setting, implementing self-organizing traffic lights in an advanced traffic simulator using real data from a Brussels avenue. On average, for different traffic densities, travel waiting times are reduced by 50% compared to the current green wave method.